Question Description

Examples to a learning task are given as pairs of numbers (x1,x2), labeled as positive or negative.

It is known that all positive examples and none of the negative examples satisfy: x1 = a, AND 0 ≤ x2 ≤ b,

Assume that a learning algorithm capable of producing a hypothesis consistent with all training examples is available. In each of the following cases compute how many randomly chosen training examples are needed to guarantee with conﬁdence of at least 90% that at least 95% of randomly selected test examples are answered correctly.

Specify the formula you use for the computation, and what is the value of each of the variables in the formula.